Eduards Sizovs - Micro Service Architecture DevConFu
Eduards will talk about micro service architecture - approach to designing software when complex app is broken into tiny, cohesive services which are apps themselves. Anatomy of micro services will be covered with practical implementation advices in Java.
Micro service architecture - building scalable web solutions - George James -...Red Blue Blur Ideas
Proper architecture is needed in building enterprise web applications to ensure that it is easily scalable and developers productivity is high. In this session we are going to be talking about:
– What is micro-service Architecture
– What problem we are trying to solve
– Benefits of working with micro-service architecture
– Analysis/Architecting a micro-service application
– How to break down a monolith to use the micro-service architecture etc.
About The Speaker:
George James bio:
George James is a Full-stack software developer at RBBI, he has a Bachelors degree in Electrical Engineering from Ahmadu Bello University but works full time as a software developer. He is experienced in PHP, JavaScript (Front), NodeJS, CSS, Kafka, Kubernetes, GRPC etc., and lots of frameworks and Libraries. George James has been writing code for over 5 years and has a strong passion to learn functional programming.
Eduards Sizovs - Micro Service Architecture DevConFu
Eduards will talk about micro service architecture - approach to designing software when complex app is broken into tiny, cohesive services which are apps themselves. Anatomy of micro services will be covered with practical implementation advices in Java.
Micro service architecture - building scalable web solutions - George James -...Red Blue Blur Ideas
Proper architecture is needed in building enterprise web applications to ensure that it is easily scalable and developers productivity is high. In this session we are going to be talking about:
– What is micro-service Architecture
– What problem we are trying to solve
– Benefits of working with micro-service architecture
– Analysis/Architecting a micro-service application
– How to break down a monolith to use the micro-service architecture etc.
About The Speaker:
George James bio:
George James is a Full-stack software developer at RBBI, he has a Bachelors degree in Electrical Engineering from Ahmadu Bello University but works full time as a software developer. He is experienced in PHP, JavaScript (Front), NodeJS, CSS, Kafka, Kubernetes, GRPC etc., and lots of frameworks and Libraries. George James has been writing code for over 5 years and has a strong passion to learn functional programming.
Performance Monitoring with AOP and Amazon CloudWatchYan Cui
This talk outlines how to easily set up pseudo-RT performance monitoring for your application using an AOP framework such as PostSharp in conjunction with the Amazon CloudWatch service.
Project Riff는 Kubernetes 기반의 함수형 서비스로 스크립트, Node.js, Spring Cloud Function로 작성된 함수를 이벤트 발생시 실행 할 수 있습니다. Riff 상에 Spring Cloud Function을 사용하여 Serverless Spring을 사용하는 방법에 대해서 살펴봅니다.
At Netflix, we provide an API that supports the content discovery, sign-up, and playback experience on thousands of device types that millions use around the world every day. As our user base and traffic has grown by leaps and bounds, we are continuously evolving this API to be flexible, scalable, and resilient and enable the best experience for our users. In this talk, I gave an overview of how and why the Netflix API has evolved to where it is today and how we make it resilient against failures while keeping it flexible and nimble enough to support continuous A/B testing.
FaaS or not to FaaS. Visible and invisible benefits of the Serverless paradig...Vadym Kazulkin
When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.
Web jobs, Azure Functions and Serverless ComputingParis Polyzos
This talk is about Serverless architectures, where applications significantly depend on third-party services or on custom code that run in ephemeral containers, managed by someone else. I focus on two Microsoft Azure services, Azure Functions and Azure WebJobs, and I describe when and how you should use each one of them.
The Netflix API Platform for Server-Side ScriptingKatharina Probst
Presented at QCon NYC 2016.
The Netflix API is the front-door for almost all device/UI requests from 1000+ device types to the Netflix backends. It serves everything from movie and show recommendations, profile, sign-up, and A/B test related functionality, to bookmarks and licenses for playback.
Because all devices use this API, and because Netflix runs on devices of widely varying sizes and interaction models, it has served us well to enable a platform against which device teams write server-side scripts. Using Netflix as an example, the goal of this talk is to explore situations in which server-side scripting is a good solution for applications. I will describe our first approach, which uses Groovy scripts. I will detail how the scripts are uploaded and can make use of shared modules. This approach allows for high flexibility and performance as well as high developer velocity, at the expense of added risk of injecting scripts into running servers. I will then dive into a new approach that will isolate the scripts into their own containers without compromising the original goals and will allow teams to write scripts in node.js, a language that is more natural for them.
Building Universal Servers (On-prem meets Azure PAAS)adamcarmi
A talk given at the Microsoft CTO breakfast club on Nov 7th 2016 which described how we designed and built the Applitools server which can be deployed and run on-prem as well as an Azure Cloud Service.
- Overview of a use case - Sentiment analysis
- Introduction - Using Jupyter Notebook & AWS SageMaker
- Setup New Project
- Setup and Run the Build CI/CD Pipeline
- Setup the Release Pipeline
- Test Build and Release Pipelines
- Testing the deployed solution
- Examining deployed model performance
Performance Monitoring with AOP and Amazon CloudWatchYan Cui
This talk outlines how to easily set up pseudo-RT performance monitoring for your application using an AOP framework such as PostSharp in conjunction with the Amazon CloudWatch service.
Project Riff는 Kubernetes 기반의 함수형 서비스로 스크립트, Node.js, Spring Cloud Function로 작성된 함수를 이벤트 발생시 실행 할 수 있습니다. Riff 상에 Spring Cloud Function을 사용하여 Serverless Spring을 사용하는 방법에 대해서 살펴봅니다.
At Netflix, we provide an API that supports the content discovery, sign-up, and playback experience on thousands of device types that millions use around the world every day. As our user base and traffic has grown by leaps and bounds, we are continuously evolving this API to be flexible, scalable, and resilient and enable the best experience for our users. In this talk, I gave an overview of how and why the Netflix API has evolved to where it is today and how we make it resilient against failures while keeping it flexible and nimble enough to support continuous A/B testing.
FaaS or not to FaaS. Visible and invisible benefits of the Serverless paradig...Vadym Kazulkin
When we talk about prices, we often only talk about Lambda costs. In our applications, however, we rarely use only Lambda. Usually we have other building blocks like API Gateway, data sources like SNS, SQS or Kinesis. We also store our data either in S3 or in serverless databases like DynamoDB or recently in Aurora Serverless. All of these AWS services have their own pricing models to look out for. In this talk, we will draw a complete picture of the total cost of ownership in serverless applications and present a decision-making list for determining if and whether to rely on serverless paradigm in your project. In doing so, we look at the cost aspects as well as other aspects such as understanding application lifecycle, software architecture, platform limitations, organizational knowledge and plattform and tooling maturity. We will also discuss current challenges adopting serverless such as lack of high latency ephemeral storage, unsufficient network performance and missing security features.
Web jobs, Azure Functions and Serverless ComputingParis Polyzos
This talk is about Serverless architectures, where applications significantly depend on third-party services or on custom code that run in ephemeral containers, managed by someone else. I focus on two Microsoft Azure services, Azure Functions and Azure WebJobs, and I describe when and how you should use each one of them.
The Netflix API Platform for Server-Side ScriptingKatharina Probst
Presented at QCon NYC 2016.
The Netflix API is the front-door for almost all device/UI requests from 1000+ device types to the Netflix backends. It serves everything from movie and show recommendations, profile, sign-up, and A/B test related functionality, to bookmarks and licenses for playback.
Because all devices use this API, and because Netflix runs on devices of widely varying sizes and interaction models, it has served us well to enable a platform against which device teams write server-side scripts. Using Netflix as an example, the goal of this talk is to explore situations in which server-side scripting is a good solution for applications. I will describe our first approach, which uses Groovy scripts. I will detail how the scripts are uploaded and can make use of shared modules. This approach allows for high flexibility and performance as well as high developer velocity, at the expense of added risk of injecting scripts into running servers. I will then dive into a new approach that will isolate the scripts into their own containers without compromising the original goals and will allow teams to write scripts in node.js, a language that is more natural for them.
Building Universal Servers (On-prem meets Azure PAAS)adamcarmi
A talk given at the Microsoft CTO breakfast club on Nov 7th 2016 which described how we designed and built the Applitools server which can be deployed and run on-prem as well as an Azure Cloud Service.
- Overview of a use case - Sentiment analysis
- Introduction - Using Jupyter Notebook & AWS SageMaker
- Setup New Project
- Setup and Run the Build CI/CD Pipeline
- Setup the Release Pipeline
- Test Build and Release Pipelines
- Testing the deployed solution
- Examining deployed model performance
Google App Engine is a platform as a service (PaaS) cloud computing platform for developing and hosting web applications in Google-managed data centers.
Cutting Edge Computer Vision for EveryoneIvo Andreev
Microsoft offers a wide range of tools and advanced solutions to support you in managing computer vision related tasks.
From purely coding approaches with ML.NET, through zero-code ComputerVision.ai to advanced and flexible AI service in Azure ML, there is a solution for every need and each type of person.
From running on premises, through managed infrastructure to completely cloud services the speed of getting to the desired results and the return of investment are guaranteed.
Join this session to get insights about the options, deployment, pricing, pros and cons compared and select the most appropriate tech for your business case.
Choosing & building the appropriate infrastructure to run your applications in production can be a daunting task. Typically we revisit previous choices as we approach different scales. In this talk we'll cover the two architectures we've been through at Workday so far and speak about our third major architectural change as we ramp up to larger numbers of servers and users. Topics will include: deployment, configuration management, automation tools, build & test pipelines, immutable infrastructure.
What Is Your PLM Challenge - Decrease downtime and minimize production problemsDawn Collins
King Automation shares how to increase business and meet customer needs, while decreasing downtime and minimizing production problems with Process Simulate. Waltonen walks through the successful implementation. Geometric Solutions is your one stop shop for PLM solutions, training and support. Moldex3D are the molding design and simulation specialists.
Evolving Services Into A Cloud Native WorldIain Hull
How Workday manage stateful services with a custom controller on Kubernetes?
Conference talk for CloudNative London 2018
https://skillsmatter.com/skillscasts/12106-evolving-services-into-the-cloud-native-world-how-workday-manage-stateful-services-with-a-custom-controller-on-kubernetes
Kubernetes and declarative infrastructure greatly simplify the way we deploy and manage software. Most services can be orchestrated with the control loops supplied by Kubernetes (deployments, stateful sets or jobs). Some stateful services in Workday require more advanced orchestration, and re-architecting them is not an easy option.
In this talk you will discover why some of our services require extra orchestration, and how we evolved an existing service into a control loop on top of Kubernetes. The control loop organises multiple services into groups these are dynamically created, deleted and scaled. It also orchestrates blue/green deployments of each group. Now we can adopt more kubernetes features and retire some of our old scheduling code. Finally you will learn the process we follow to evaluate and design our own control loops and when you might find them useful.
Bio
Iain is a principal software engineer at Workday using Kubernetes and Scala to deliver their next generation elastic grid. His twin passions are large scale distributed computing and applying clean code to complex problems. He is interested in good design and how this can improve system reliability and reduce friction during development.
He loves sharing his experiences as he learns and builds new systems. He regularly speaks at local meetups in Dublin and has presented at conferences including GotoConf, Scala Days, Functional Kats and Lambda World.
Application Architecture Summit - Monitoring the Dynamic Cloud New Relic
How do you apply modern application to your digital business? Hear from New Relic's Sr Director, Strategic Architecture, Lee Atchison, at the Application Architecture Summit. Learn more here: https://newrelic.com/partner/aws
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
3. Who am I?
Kazuyuki Miyazawa
Work Experience
• April 2019 - Present
AI Research Engineer @DeNA Co., Ltd.
• April 2010 - March 2019
Research Scientist @Mitsubishi Electric Corp.
Education
• PhD in Information Science @Tohoku Univ.
@kzykmyzw
4. Background
•Maps are an essential ingredient for every mobility service
•Higher & higher map quality is in demand to enable advanced services
(e.g., autonomous vehicle)
-1980s 1980s-20XXs 20XXs-
5. Problems for Current Map Creation/Maintenance
•Manual processes are labor-intensive and time-consuming
•Using a special measurement system (e.g., mobile mapping system) is costly and
difficult to scale to achieve high coverage for various types of mobility services
https://www.infradoctor.jp/details/detail20190313.pdf
https://www.google.com/streetview/explore/
6. What Can DeNA Do About It?
•Dashcams are becoming popular, and can capture a lot of useful information for maps
•Current AI shows an amazing performance for image/video analysis
•We are developing low-cost and rapid map creation (or maintenance) technology
using dashcam videos collected via cloud servers
2014 2015 2016 2017 2018
160
120
80
40
0
Dashcam sales volume (Japan)(million units)
GfKジャパン, “2018年ドライブレコーダーの販売動向,” 2019
https://www.gfk.com/fileadmin/user_upload/dyna_content/JP/20190328_drivinngrecorders.pdf
9. How Do We Know the 3D Position from a 2D
Image?
?
?
?
From a single 2D image, we cannot
decide the 3D position of the object
10. How Do We Know the 3D Position from 2D Images?
If we have two (or more) views, we can
decide the 3D object position as the
intersection of camera rays
11. Dashcam Video = Multi-View Images
time: t1
time: t2
time: t3
Dashcam video can be seen as a set of
multi-view images because the vehicle
moves while capturing
12. Dashcam Video = Multi-View Images
time: t1
time: t2
time: t3
Dashcam video can be seen as a set of
multi-view images because the vehicle
moves while capturing
Camera pose for each frame is
necessary to calculate the 3D
object position
13. Camera Pose Estimation from Video
•SfM*1 or Visual SLAM*2 is used as a core technology
•Estimate the camera poses by tracking salient points in the video
*1 Structure from Motion
*2 Simultaneous Localization And Mapping
15. Dataset Creation for Accuracy Evaluation
•Built our own dataset of dashcam videos and corresponding highly accurate 3D data
as ground truth for evaluation purposes
•Manually annotated various objects (e.g., traffic signs, lanes, etc.)
Videos from Dashcams 3D Point Clouds from LiDAR
16. Sample Results
Dashcam Video Estimated Position
Estimated camera positions
Estimated object position
Ground-truth object position
Error: 0.20m
17. Sample Results
Dashcam Video Estimated Position
Estimated camera positions
Estimated object position
Ground-truth object position
Error: 1.2m
18. Results Summary
0 0.5 1.0 1.5 2.0 2.5
Error [m]
Frequency
Average Error: 0.74m
Average error of object position estimation is below 1m!
20. Of Course, Deep Learning!
R-FCN: Object Detection via Region-based Fully ConvolutionalNetworks
https://arxiv.org/pdf/1605.06409v2.pdf
OpenPose: RealtimeMulti-Person 2D Pose Estimation using Part AffinityFields
https://arxiv.org/pdf/1812.08008.pdf
Panoptic Segmentation
https://arxiv.org/pdf/1801.00868.pdf
21. Traffic Light/Sign Detection using CNN
• Use Faster R-CNN to detect traffic lights/signs in each frame of dashcam videos
• Faster R-CNN is one of the most successful object detection methods proposed in 2016
• Main drawback is speed, but acceptable for off-line applications
Classification
Regression
Traffic light
Stop
Speed limit
No right turn
Position
…
CNN
Region Proposals
24. Q. Is It Easy to Achieve This? A. NO!
Data
Preparation
Model
Training
Parameter
Tuning
Model
Verification
Deploy
Monitoring Data Analysis
Model
Development
Need to iterate again and again
25. Q. Is It Easy to Achieve This? A. NO!
Data
Preparation
Model
Training
Parameter
Tuning
Model
Verification
Deploy
Monitoring Data Analysis
Model
Development
Rapid iteration is the key
26. Who am I?
Profile
• Kosuke Kuzuoka (23)
• Love Tesla, Elon Musk and cats
Experience
• February 2020 - Present
Software Engineer, ML @Mercari, Inc.
• June 2018 – February 2020
AI Research Engineer @DeNA Co., Ltd.
• March 2017 – June 2018
R&D Manager @Photoruction, inc.
27. Brief Intro to Object Detection
• An active research area among
computer vision community
• Task is detecting objects
(like cats) in an image
• Modern algorithms heavily
rely on deep learning
• Takes hours to train a model
Photo by Paul Hanaoka on Unsplash
28. Photo by Paul Hanaoka on Unsplash
A cat is detected as a cat,
hence it’s a true positive.
Wrongly detected as cats,
hence they are false positives
29. Problems in Development Processes
1. Train, validate and test models (computationally expensive)
2. Evaluate, visualize and analyze models (time consuming)
3. Adjust hyper-param, then go back to 1
30. Problems in Development Processes
1. Train, validate and test models (computationally expensive)
2. Evaluate, visualize and analyze models (time consuming)
3. Adjust hyper-param, then go back to 1
31. Problems in Development Processes
1. Train, validate and test models (computationally expensive)
2. Evaluate, visualize and analyze models (time consuming)
3. Adjust hyper-param, then go back to 1
32. Problems in Development Processes
1. Train, validate and test models (computationally expensive)
2. Evaluate, visualize and analyze models (time consuming)
3. Adjust hyper-param, then go back to 1
33. Problems in Development Processes
1. Train, validate and test models (computationally expensive)
2. Evaluate, visualize and analyze models (time consuming)
3. Adjust hyper-param, then go back to 1
Not essential, yet
very important...
34. Some of Problems are:
• Error-prone process (misspelling commands, etc.)
• Going back and forth between EC2 instances…
• Inefficient process, like drawing boxes, uploading
to third party app for visualization etc.
• Researchers not being able to focus on essential
work (developing models etc.)
35. Solutions!
• Work harder and harder...
• Automating tasks via workflow engine
• Flexible internal tool to evaluate,
visualize and analyze models
36. Solutions!
• Work harder and harder...
• Automating tasks via workflow engine
• Flexible internal tool to evaluate,
visualize and analyze models But I’m busy
with AI dev...
37. What We Wanted...
• A system that automatically evaluates,
visualizes and analyzes models and datasets.
• A tool that lets researchers focus on
essential work (parameter tuning etc.)
• User-friendly web app
38. • Easy to develop
• Easy to collaborate
• Good performance
• AI engineer friendly
(Python… )
Yet, We Want It to Be:
40. • Easy to deploy and maintain
• Collaborations made easy
• Cost effective, yet performant
• You can use Python
Image source: https://serverless.com/
41. Serverless Computing
• No need to manage servers,
cloud providers do it for you!
• Consists of small deployable
unit of functions
• Scales as your app grows
• No idle fee, pay as you go
42. • No need to manage servers,
cloud providers do it for you!
• Consists of small deployable
unit of functions
• Scales as your app grows
• No idle fee, pay as you go
Serverless Computing
Image source: https://aws.amazon.com/
43. • No need to manage servers,
cloud providers do it for you!
• Consists of small deployable
unit of functions
• Scales as your app grows
• No idle fee, pay as you go
Serverless Computing
44. • No need to manage servers,
cloud providers do it for you!
• Consists of small deployable
unit of functions
• Scales as your app grows
• No idle fee, pay as you go
Serverless Computing
45. Serverless Computing
• No need to manage servers,
cloud providers do it for you!
• Consists of small deployable
unit of functions
• Scales as your app grows
• No idle fee, pay as you go
58. More Functionalities On Its Way...
• Model version control
• Dataset analysis and version control
• Automating training and testing
59. Summing It Up
• Speed is important. You don’t want to
spend too much time on an internal tool
• Collaboration should be easy. Every
engineer should be able to contribute
• With little effort, researchers can focus
on more essential work
60. Wrap Up
AI Technologies for Map Creation/Maintenance
• Dashcam videos contain a lot of useful information for maps
• Develop computer vision technology to estimate objects’ positions
• Experimental evaluation shows the estimation error is less than 1m
Engineering for Continuous Improvement
• Rapid development cycle is important
• Serverless architecture is a cost-effective choice to develop and maintain
support tools for continuous improvement of AI